research
∙
06/20/2023
Minimum Eigenvalue Based Covariance Matrix Estimation with Limited Samples
In this paper, we consider the interference rejection combining (IRC) re...
share
research
∙
01/25/2023
Language Model Detoxification in Dialogue with Contextualized Stance Control
To reduce the toxic degeneration in a pretrained Language Model (LM), pr...
research
∙
10/13/2022
Explanations from Large Language Models Make Small Reasoners Better
Integrating free-text explanations to in-context learning of large langu...
research
∙
10/09/2022
Controllable Dialogue Simulation with In-Context Learning
Building dialogue systems requires a large corpus of annotated dialogues...
research
∙
08/09/2022
Limitations of Language Models in Arithmetic and Symbolic Induction
Recent work has shown that large pretrained Language Models (LMs) can no...
research
∙
02/27/2022
Controllable Natural Language Generation with Contrastive Prefixes
To guide the generation of large pretrained language models (LM), previo...
research
∙
07/20/2021
Readability Research: An Interdisciplinary Approach
Readability is on the cusp of a revolution. Fixed text is becoming fluid...
research
∙
06/05/2021
Lifelong Learning of Hate Speech Classification on Social Media
Existing work on automated hate speech classification assumes that the d...
research
∙
04/13/2021
Lets Make A Story Measuring MR Child Engagement
We present the result of a pilot study measuring child engagement with t...
research
∙
11/09/2019
Towards Understanding Gender Bias in Relation Extraction
Recent developments in Neural Relation Extraction (NRE) have made signif...
research
∙
09/10/2019
A Benchmark Dataset for Learning to Intervene in Online Hate Speech
Countering online hate speech is a critical yet challenging task, but on...
research
∙
04/04/2019
Learning to Decipher Hate Symbols
Existing computational models to understand hate speech typically frame ...
research
∙
11/02/2018
A Survey on Natural Language Processing for Fake News Detection
Fake news detection is a critical yet challenging problem in Natural Lan...
research
∙
08/31/2018
Hierarchical CVAE for Fine-Grained Hate Speech Classification
Existing work on automated hate speech detection typically focuses on bi...
research
∙
04/25/2018
Wireless Quantization Index Modulation: Enabling Communication Through Existing Signals
As the number of IoT devices continue to exponentially increase and satu...
research
∙
04/09/2018
Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection
Hate speech detection is a critical, yet challenging problem in Natural ...
research
∙
08/26/2016
Clustering and Community Detection with Imbalanced Clusters
Spectral clustering methods which are frequently used in clustering and ...
research
∙
01/22/2016
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs
We propose a non-parametric anomaly detection algorithm for high dimensi...
research
∙
02/06/2015
Learning Efficient Anomaly Detectors from K-NN Graphs
We propose a non-parametric anomaly detection algorithm for high dimensi...
research
∙
11/23/2014
Efficient Minimax Signal Detection on Graphs
Several problems such as network intrusion, community detection, and dis...
research
∙
05/02/2014
A Rank-SVM Approach to Anomaly Detection
We propose a novel non-parametric adaptive anomaly detection algorithm f...
research
∙
09/09/2013
Spectral Clustering with Imbalanced Data
Spectral clustering is sensitive to how graphs are constructed from data...
research
∙
02/20/2013
Spectral Clustering with Unbalanced Data
Spectral clustering (SC) and graph-based semi-supervised learning (SSL) ...
research
∙
05/07/2012
Graph-based Learning with Unbalanced Clusters
Graph construction is a crucial step in spectral clustering (SC) and gra...
research
∙
12/11/2011